Spatiotemporal Modeling of Ambient Sulfur Dioxide Concentrations in Rural Western Canada

The provinces of Saskatchewan, Alberta, and British Columbia are major oil- and gas-producing regions in western Canada. With increasing oil and gas production activities, there has been a growing concern of the effect of oil and gas industry emissions on health. Nevertheless, lack of proper tools to estimate the exposure to these emissions has been a hindrance to epidemiological studies and risk assessment. This paper presents a spatiotemporal modeling approach to estimating ambient sulfur dioxide (SO₂) levels based on environmental monitoring data (N = 10,295), which were collected at rural sites (591 per month on average) of this region from June 1, 2001 to May 31, 2002. Based on the model, illustrative maps consistently revealed high and low SO₂ concentration sub-regions. The sub-regions with elevated SO₂ concentrations had increased levels during the winter months from December 2001 to March 2002 and then decreased during the spring of 2002. This statistical modeling approach may help researchers estimate the SO₂ levels within the study area for their epidemiological studies or risk assessment.     

Short-term Emissions of Ammonia and Carbon Dioxide from Cattle Urine Contaminated Tropical Grassland Microcosm

The study was designed to understand the emissions of ammonia (NH₃) and carbon dioxide (CO₂) from a single cattle urination event on a tropical grassland and underline the significance of the emissions in the context of huge animal population grazing on large pasture areas in some countries. Emissions of ammonia (NH₃) and carbon dioxide (CO₂) were monitored for three weeks from a tropical grassland (dominated by Cynodon dactylon Pers.) microcosm contaminated with cow and buffalo urine. The grassland microcosms were treated with urine (50 and 100 ml of each) only once and irrigated with water once every week. Ammonia was sampled by an automatic sampling system comprising of a vacuum pump, three-way stopcocks and rubber tubing and an impinger containing suitable absorbing solution (H₂SO₄), connected to the tubing suitably. The sampled gas, after sucked by the vacuum pump and absorbed in H₂SO₄, was allowed to enter the closed microcosm again maintaining internal pressure of the microcosm. Carbon dioxide was sampled by absorption in an alkali (NaOH) trap inside the microcosm. Both NH₃ and CO₂ emissions were highly variable temporally and there was no continuous increasing or decreasing emission trend with time. Respectively, 45 and 46% of total NH₃-N were emitted within first 48 h from 50 and 100 ml cow urine application while the corresponding values for buffalo urine were 34 and 32%. Total NH₃-N emissions, integrated for sampling days (i.e. 1, 2, 3, 4, 6, 15, 18 and 21st) were 11 and 6% in cow and 8 and 5% in buffalo urine, of the total-N added through 50 and 100 ml urine samples. Carbon dioxide emissions were standardized at 25 ^∘C by using a suitable formula which were lower than actual emissions at actual soil temperature (> 25 ^∘C). Carbon dioxide emission rates were classified on the basis of soil repiratory classification and classes ranged from moderately low soil activity up to unusually high soil activity, the latter observed only on very few sampling days. Grasses in the microcosm had shown appreciable growth after urine application. Although variable and somewhat unpredictable, emissions were appreciable and that too only from a patch of single urination, indicating to the huge magnitude of total emissions under the scenario of thousands of cattle grazing on hundreds of acres of grasslands in a tropical country.     

Spatial Modeling of Mean Annual Temperature in Iran: Comparing Cokriging and Geographically Weighted Regression

Mapping spatial distribution of climatological parameters with a good degree of accuracy is crucial in environmental modeling and planning. Nowadays, there are various models to estimate and predict spatial variables in an area but some such as cokriging and geographically weighted regression (GWR) have got more attention from experts in this field. The objectives of this study are to evaluate and compare GWR with ordinary cokriging (OCK) techniques for estimating the mean annual air temperature (MAT) of Iran using European Centre for Medium-Range Weather Forecasts (ECMWF) data and auxiliary variables (e.g., longitude, latitude and altitude). The MAT-gridded data for Iran was collected in pixels during the time interval of 1987–2015 from the ERA-Interim re-analysis version of ECMWF. Validation results indicate that cokriging model with latitude and altitude for estimating MAT has the lowest MAE (0.0155), MBE (0.00085), RMSE (0.0251), and the highest NS (0.9999) in relation to other cokriging methods. On the other hand, GWR with altitude has better results than those of GWR with other auxiliary variables because of its MAE (0.1271), MBE (0.0124), RMSE (0.1760), and NS (0.9969). By comparing two mentioned methods, cokriging with latitude and altitude has provided the best performance in relation to GWR for prediction of MAT in Iran. To obtain accurate estimation of the spatial distribution of MAT, local residuals were analyzed. Results concluded that residuals of the OCK model have high spatial adaptations between the observed and predicted MAT data compared to the GWR model. Hence, OCK was a relatively optimum method for the estimation of MAT compared with GWR.

     

Spatial Distribution of the Annual Atmospheric Carbon Dioxide in the Contiguous USA and Their Controlling Factors

Environmental Modeling & Assessment - Analyzing the geographical distribution of carbon dioxide (CO2) is essential for understanding the influence and structural nature of area-specific...     

Attribution of Carbon Dioxide Fluxes to Crop Types in a Heterogeneous Agricultural Landscape of Argentina

The increasing proportion of agricultural lands worldwide makes it necessary to intensify the research concerning the carbon exchange at agricultural sites. In order to determine the Net Ecosystem Exchange (NEE) in an agricultural landscape in the province of Buenos Aires, Argentina, we carried out eddy covariance measurements with a flux tower, which was placed between two agricultural fields. Therefore, the measured CO₂ flux represents the accumulated flux from both areas, i.e., from different crop types. We here present an analysis method which attributes the flux to the two crop types. For this analysis, we applied the Hsieh footprint model to identify the contributing source area to the flux measurement. We then applied a multiple regression analysis to calculate the NEE in the growing season 2011/2012 for each field separately. The pronounced differences in the time courses of the CO₂ fluxes in the two fields can be explained by the different sowing times and different growth stages of both cultivations. The time courses furthermore show that the CO₂ uptake of the plants was strongly affected by the drought which lasted from December 2011 to January 2012. For the growth cycle of maize (216 days), the NEE was ?240 g C m^?2 and for the growth cycle of soybean (154 days) ?231 g C m^?2. In order to obtain the NEE of a complete agricultural cycle (from harvest to harvest), we also considered the NEE of autumn and winter 2011. Uncertainties of the spatially partitioned NEE are quantified and discussed.     

Modeling a Carbon Capture,Transport, and Storage Infrastructure for Europe

In this paper, we develop a model to analyze the economics of carbon capture, transport, and storage (CCTS) in the wake of expected rising CO₂ prices. We present a scalable mixed integer, multiperiod, welfare-optimizing network model for Europe, called CCTS-Mod. The model incorporates endogenous decisions on carbon capture, pipeline and storage investments, as well as capture, flow and injection quantities based on given costs, CO₂ prices, storage capacities, and point source emissions. Given full information about future costs of CCTS-technology, and CO₂ prices, the model determines a cost minimizing strategy on whether to purchase CO₂ certificates, or to abate the CO₂ through investments into a CCTS-chain on a site by site basis. We apply the model to analyze different scenarios for the deployment of CCTS in Europe, e.g., under high and low CO₂ prices, respectively. We find that beyond CO₂ prices of €50 per t, CCTS can contribute to the decarbonization of Europe’s industry sectors, as long as one assumes sufficient storage capacities (onshore and/or offshore). We find that CCTS is only viable for the power sector if the CO₂ certificate price exceeds €75 per t.     

张掖市SO2控制区污染源的解析

张掖市是国务院划定的SO2污染控制区之一,其SO2污染严重程度居全国前列,本研究以环境空气SO2监测和SO2污染源监测调查为基础,以ATDL模式为模拟手段,对张掖市SO2控制区的污染源进行了解析,分析找出造成该控制区SO2污染的根本原因,从而为制定SO2污染总量控制方案奠定科学基础。     

The Climate Impacts of Sulfate Aerosols

Sulfate aerosols (SO₄) from anthropogenic emissions of sulfur dioxide (SO₂) generally have a cooling effect. However, if SO₂ emissions fall over time, accounting for sulfate aerosols will increase the predicted warming from greenhouse gases. This paper integrates the four marker emission scenarios for CO₂ and SO₄ from the Special Report on Emissions Scenarios (SRES), the UIUC general circulation model (GCM), and a country-specific impact model (GIM) to calculate the impacts of sulfate aerosols. By 2100, lower SO₂ emissions slightly increase warming in the temperate and polar regions causing small damages in the former and small benefits in the latter. If SO₂ emissions are also lower in tropical regions, temperatures will rise causing small damages there as well. However, if SO₂ emissions rise in tropical regions, temperatures will fall leading to small benefits. This revised version was published online in July 2006 with corrections to the Cover Date.     

The Impact of Income Inequality on Carbon Emissions in Asian Countries: Non-Parametric Panel Data Analysis

Environmental Modeling & Assessment - Widening income inequality and environmental degradation are two of the most important problems that threat the sustainable development. For that, this...     

Quantifying Land-Use Alterations and Associated Hydrologic Impacts at a Wetland Area by Using Remote Sensing and Modeling Techniques

Land use changes and associated hydrologic disturbances, mainly caused by human activities, is a common reason for wetlands degradation worldwide. The particular scientific effort utilized remotely sensed data, GIS techniques and hydrologic modeling to estimate land use alterations during a 40-years period as well as associated changes in hydrologic parameters such as overland and underground flow, infiltration, evapotranspiration and water storages on ground surface. The results indicated significant variations in the hydrologic regime including a 6% increase in the annual evapotranspiration and a 10% increase in the soil water deficit that impose substantial impacts on the regional wetlands.     

Modeling of Ecological Footprint and Climate Change Impacts on Food Security of the Hill Tracts of Chittagong in Bangladesh

This paper presents an integrated and dynamic model for the management of the uplands of the Hill Tracts of Chittagong to predict food security and environmental loading for gradual transition of shifting agriculture land into horticulture crops and teak plantation, and crop land into tobacco cultivation. Food security status for gradual transmission of shifting agriculture land into horticulture crops and teak plantation, and crop land into tobacco cultivation is the best option for food security, but this causes the highest environmental loading resulting from tobacco cultivation. Considering both food security and environmental degradation in terms of ecological footprint, the best option is gradual transition of shifting agriculture land into horticulture crops which provides moderate increase in the food security with a relatively lower environmental degradation in terms of ecological footprint. Crop growth model InfoCrop was used to predict the climate change impacts on rice and maize production in the uplands of the Hill Tracts of Chittagong. Climate change impacts on the yields of rice and maize of three treatments of temperature, carbon dioxide and rainfall change (+0 °C, +0 ppm and +0 % rainfall), (+2 °C, +50 ppm and 20 % rainfall) and (+2 °C, +100 ppm and 30 % rainfall) were assessed. The yield of rice decreases for treatment 2, but it increases for treatment 3. The yield of maize increases for treatments 2 and 3 since maize is a C₄ plant. There is almost no change in food security at upazila (sub-district) level for the historical climate change scenario, but there is small change in the food security at upazila levels for IPCC climate change scenario.     

环境空气中二氧化硫24 h连续采样存在的问题

针对二氧化硫24h连续采样过程中发现的问题,进行不同方式的模拟实验。结果表明,气样引入方式,空气温,湿度以及气体吸收液的动态稳定性均对采样效率有影响;甲醛吸收液对低浓度二氧化硫的吸收效率较低。对如何提高二氧化硫采样效率提出了几点建议。     

NEMS and MARKAL-MACRO Models for Energy-Environmental-Economic Analysis: A Comparison of the Electricity and Carbon Reduction Projections

The Annual Energy Outlook forecasts published by the United States Energy Information Administration (EIA) of the Department of Energy are based on results from the National Energy Modeling system (NEMS). This paper compares NEMS, which is used only in the U.S., with the U.S. version of MARKAL-MACRO (USMM) model, which is used in more than thirty-five countries. The two models predict similar results for the base 1999 US Annual Energy Outlook (AEO), but their results with carbon constraints are quite different. The differences of the models and those of their predictions are explained. USMM can be used to provide an alternative and complementary approach to projections of renewable technologies penetration and their potential in reducing carbon dioxide emissions in the USA.     

Time-Frequency Analysis of the Relationship Between EUA and CER Carbon Markets

In this paper, interactions or co-movement between the CER and EUA futures prices are examined in order to shed light on the dependency between the European Union Emissions Trading Scheme (EU ETS) and the clean development mechanism (MDP). Our analysis uses the wavelet method to model the correlation between CER and EUA in the time-frequency domain. It highlights the impact of different investors (according to their investment horizons) on the co-movement between the CER and EUA prices, and therefore, the behavior of individual investors as speculators, arbitrageurs, and hedgers on European allowance and CDM credits cumulatively. In this vein, we analyze according to the frequency intervals, price convergence, identification of potential factors that could explain a difference in futures prices, and structural changes in the EUA and CER prices. The application is made using daily EUA’s and CER’s prices data.     

Bivariate Extreme Value Analysis of Rainfall and Temperature in Nigeria

Environmental Modeling & Assessment - The rising cases of floods and the onset of drought in different parts of Nigeria require urgent attention particularly because Nigeria accommodates the...     

Marginal Abatement Costs and Marginal Welfare Costs for Greenhouse Gas Emissions Reductions: Results from the EPPA Model

Marginal abatement cost (MAC) curves, relationships between tonnes of emissions abated and the CO₂ (or greenhouse gas (GHG)) price, have been widely used as pedagogic devices to illustrate simple economic concepts such as the benefits of emissions trading. They have also been used to produce reduced-form models to examine situations where solving the more complex model underlying the MAC is difficult. Some important issues arise in such applications: (1) Are MAC relationships independent of what happens in other regions?, (2) are MACs stable through time regardless of what policies have been implemented in the past?, and (3) can one approximate welfare costs from MACs? This paper explores the basic characteristics of MAC and marginal welfare cost (MWC) curves, deriving them using the MIT Emissions Prediction and Policy Analysis model. We find that, depending on the method used to construct them, MACs are affected by policies abroad. They are also dependent on policies in place in the past and depend on whether they are CO₂-only or include all GHGs. Further, we find that MACs are, in general, not closely related to MWCs and therefore should not be used to derive estimates of welfare change. We also show that, as commonly constructed, MACs may be unreliable in replicating results of the parent model when used to simulate GHG policies. This is especially true if the policy simulations differ from the conditions under which the MACs were simulated.